Descripción de la oferta
We are seeking a talented Computer Vision Researcher to join our team.As a Computer Vision Expert, you will have the following responsibilities and challenges:Research: Study and apply classical computer vision and optimization algorithms to improve system componentsDevelop: Create reliable and efficient Machine Learning models for object detection, segmentation, and classificationDesign: Devise intelligent methods for building relevant and qualitative datasetsSolve: Apply state-of-the-art methods to address unique challenges in the wood industryScale: Enhance the scalability of ML solutionsInnovate: Develop accurate and efficient 3D modeling techniques using stereo vision, structured light, and MLWe work in small teams with a startup mentality. We are a horizontal organization where originality and self-drive are valuable assets that we encourage. Our team members have diverse research and technical backgrounds in various complementary fields. You will have a key position in designing and building innovative products.Our clients are the largest lumber sawmills worldwide. These companies play a key role in the transition to a carbon-neutral world, and we help them bring innovation, technology, and automation to drive efficiency and reduce waste.A typical candidate wouldhave experience in Classical Computer Vision and Machine Learninghave experience working with large datasetsdraw data-driven conclusions using statistical inferencehave programming experience in Python and Javahave hands-on experience with Tensorflow or PyTorchbe self-driven and able to independently carry a task to completionbe pragmatic and goal-orientedThe ideal candidate wouldhave a PhD in a STEM field or 3-year experience in a research position in the industryhave an advanced understanding of deep learning techniques applied to computer vision problemsenjoy reading the latest academic papers in the fieldhave implemented computer vision algorithms in an industrial setting (wood industry would be perfect)thrive in a client-driven research environment that requires perseverance and creative solutionsBenefitstraining, knowledge